Improving Hydrologic Prediction at the Basin Scale through State Updating

Abstract:

Data assimilation (DA) holds considerable potential for improving hydrologic predictions. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. Several challenges exist (see Liu et al., 2012). The objective of this paper is to highlight several recent studies on basin scale data assimilation using distributed hydrologic models that touch upon these challenges including application of streamflow data assimilation using different algorithms, combined streamflow/snow data assimilation and the development of a generic linkage of OpenDA and the open source hydrologic package Openstreams/Wflow based on the (emerging) standard Basic Model Interface (BMI) as advocated by CSDMS using cross-platform webservices (i.e. Apache Thrift).

Liu et al., 2012. Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities, Hydrol. Earth Syst. Sci., 16, 3863–3887, doi:10.5194/hess-16-3863-2012.